Submit to Entropy Review for Entropy Propose a Special Issue

Journal Browser

► Journal Browser

Complex Systems Time Series Analysis and Modeling for Geoscience

Print Special Issue Flyer
Special Issue Editors
Special Issue Information
Keywords
Related Special Issue
Published Papers

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Complexity".

Deadline for manuscript submissions: closed (13 September 2021) | Viewed by 26148

Share This Special Issue

Special Issue Editor

Prof. Dr. Stelios M. Potirakis

E-Mail Website
Guest Editor

1. Department of Electrical and Electronics Engineering, University of West Attica, Ancient Olive Grove Campus, GR-12241 Aigaleo, Greece
2. Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing, National Observatory of Athens, Metaxa and Vasileos Pavlou, GR-15236 Penteli, Greece
Interests: digital signal processing; complex systems time series analysis; nonlinear dynamics; criticality; precursors of extreme events; physics of earthquakes; seismo-electromagnetics; biosignal analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear colleagues,

The relatively new field of complex systems is rapidly evolving, finding applications in all types of natural, artificial and social systems. Typical examples include the different components of the Earth system, such as the atmosphere, biosphere, cryosphere, lithosphere, oceans, the near-Earth electromagnetic environment, etc., as well as their interaction. Since “controllable” laboratory conditions are not possible in a study of the Earth system, one has to rely on an analysis of the time series of any available (ground-based or remote sensing) observables and corresponding modeling of the underlying non-linear processes involved. This renders complex systems time series analysis and modeling methods particularly useful for the study and understanding of the physics of different geomagnetic, climatic and lithospheric phenomena, particularly in the study of extreme events (e.g., earthquakes, magnetic storms, rain storms, etc.) and their precursors. Finally, the scale-free nature of some of these phenomena, e.g., fractures at different spatial scales, permits the extraction of interesting information about geophysical-scale phenomena by studying the corresponding laboratory-scale phenomena by means of the same methods.

The aim of this Special Issue is to is to highlight the research topic of complex systems time series analysis and modeling for geoscience and to collect original contributions on this topic. Researchers are encouraged to present the most recent developments in both theoretical and experimental studies aimed at understanding different non-linear phenomena of the complex Earth system and its components, while laboratory-scale studies, where applicable, are also welcome.

Prof. Dr. Stelios M. Potirakis
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

complex systems
time series analysis
nonlinear dynamics
seismo-electromagnetics
acoustic emissions
natural and man-induced earthquakes
material fracture
geomagnetic phenomena
climatic phenomena
applications

Related Special Issue

Complex Systems Time Series Analysis and Modeling for Geoscience II in Entropy

Published Papers (10 papers)

Download All Papers

Research

22 pages, 7770 KiB

Open AccessArticle

Unusual Surface Latent Heat Flux Variations and Their Critical Dynamics Revealed before Strong Earthquakes

by Soujan Ghosh, Swati Chowdhury, Subrata Kundu, Sudipta Sasmal, Dimitrios Z. Politis, Stelios M. Potirakis, Masashi Hayakawa, Suman Chakraborty and Sandip K. Chakrabarti

Entropy 2022, 24(1), 23; https://doi.org/10.3390/e24010023 - 23 Dec 2021

Cited by 19 | Viewed by 2725

Abstract

We focus on the possible thermal channel of the well-known Lithosphere–Atmosphere–Ionosphere Coupling (LAIC) mechanism to identify the behavior of thermal anomalies during and prior to strong seismic events. For this, we investigate the variation of Surface Latent Heat Flux (SLHF) as resulting from satellite observables. We demonstrate a spatio-temporal variation in the SLHF before and after a set of strong seismic events occurred in Kathmandu, Nepal, and Kumamoto, Japan, having magnitudes of 7.8, 7.3, and 7.0, respectively. Before the studied earthquake cases, significant enhancements in the SLHF were identified near the epicenters. Additionally, in order to check whether critical dynamics, as the signature of a complex phenomenon such as earthquake preparation, are reflected in the SLHF data, we performed a criticality analysis using the natural time analysis method. The approach to criticality was detected within one week before each mainshock. Full article

(This article belongs to the Special Issue Complex Systems Time Series Analysis and Modeling for Geoscience)

► Show Figures

Figure 1

16 pages, 4532 KiB

Open AccessArticle

Analysis of Korean Peninsula Earthquake Network Based on Event Shuffling and Network Shuffling

by Seungsik Min and Gyuchang Lim

Entropy 2021, 23(9), 1236; https://doi.org/10.3390/e23091236 - 21 Sep 2021

Cited by 1 | Viewed by 1864

Abstract

In this work, a Korean peninsula earthquake network, constructed via event-sequential linking known as the Abe–Suzuki method, was investigated in terms of network properties. A significance test for these network properties was performed via comparisons with those of two random networks, constructed from two approaches, that is, EVENT (SEQUENCE) SHUFFLING and NETWORK (MATRIX) SHUFFLING. The Abe–Suzuki earthquake network has a clear difference from the two random networks. However, the two shuffled networks exhibited completely different functions, and even some network properties for one shuffled datum are significantly high and those of the other shuffled data are low compared to actual data. For most cases, the event-shuffled network showed a functional similarity to the real network, but with different exponents/parameters. This result strongly claims that the Korean peninsula earthquake network has a spatiotemporal causal relation. Additionally, the Korean peninsula network properties are mostly similar to those found in previous studies on the US and Japan. Further, the Korean earthquake network showed strong linearity in a specific range of spatial resolution, that is, 0.20°~0.80°, implying that macroscopic properties of the Korean earthquake network are highly regular in this range of resolution. Full article

(This article belongs to the Special Issue Complex Systems Time Series Analysis and Modeling for Geoscience)

► Show Figures

Figure 1

8 pages, 1475 KiB

Open AccessArticle

Lorenz-63 Model as a Metaphor for Transient Complexity in Climate

by Sergey Kravtsov and Anastasios A. Tsonis

Entropy 2021, 23(8), 951; https://doi.org/10.3390/e23080951 - 25 Jul 2021

Cited by 1 | Viewed by 2258

Abstract

Dynamical systems like the one described by the three-variable Lorenz-63 model may serve as metaphors for complex natural systems such as climate systems. When these systems are perturbed by external forcing factors, they tend to relax back to their equilibrium conditions after the forcing has shut off. Here we investigate the behavior of such transients in the Lorenz-63 model by studying its trajectories initialized far away from the asymptotic attractor. Counterintuitively, these transient trajectories exhibit complex routes and, in particular, the sensitivity to initial conditions is akin to that of the asymptotic behavior on the attractor. Thus, similar extreme events may lead to widely different variations before the perturbed system returns back to its statistical equilibrium. Full article

(This article belongs to the Special Issue Complex Systems Time Series Analysis and Modeling for Geoscience)

► Show Figures

Figure 1

18 pages, 11006 KiB

Open AccessFeature PaperArticle

Assessing Earthquake Forecast Performance Based on b Value in Yunnan Province, China

by Rui Wang, Ying Chang, Miao Miao, Zhiyi Zeng, Hongyan Chen, Haixia Shi, Danning Li, Lifang Liu, Youjin Su and Peng Han

Entropy 2021, 23(6), 730; https://doi.org/10.3390/e23060730 - 8 Jun 2021

Cited by 16 | Viewed by 3025

Abstract

Many studies have shown that b values tend to decrease prior to large earthquakes. To evaluate the forecast information in b value variations, we conduct a systematic assessment in Yunnan Province, China, where the seismicity is intense and moderate–large earthquakes occur frequently. The catalog in the past two decades is divided into four time periods (January 2000–December 2004, January 2005–December 2009, January 2010–December 2014, and January 2015–December 2019). The spatial b values are calculated for each 5-year span and then are used to forecast moderate-large earthquakes (M ≥ 5.0) in the subsequent period. As the fault systems in Yunnan Province are complex, to avoid possible biases in b value computation caused by different faulting regimes when using the grid search, the hierarchical space–time point-process models (HIST-PPM) proposed by Ogata are utilized to estimate spatial b values in this study. The forecast performance is tested by Molchan error diagram (MED) and the efficiency is quantified by probability gain (PG) and probability difference (PD). It is found that moderate–large earthquakes are more likely to occur in low b regions. The MED analysis shows that there is considerable precursory information in spatial b values and the forecast efficiency increases with magnitude in the Yunnan Province. These results suggest that the b value might be useful in middle- and long-term earthquake forecasts in the study area. Full article

(This article belongs to the Special Issue Complex Systems Time Series Analysis and Modeling for Geoscience)

► Show Figures

Figure 1

26 pages, 8797 KiB

Open AccessArticle

Statistical and Criticality Analysis of the Lower Ionosphere Prior to the 30 October 2020 Samos (Greece) Earthquake (M6.9), Based on VLF Electromagnetic Propagation Data as Recorded by a New VLF/LF Receiver Installed in Athens (Greece)

by Dimitrios Z. Politis, Stelios M. Potirakis, Yiannis F. Contoyiannis, Sagardweep Biswas, Sudipta Sasmal and Masashi Hayakawa

Entropy 2021, 23(6), 676; https://doi.org/10.3390/e23060676 - 27 May 2021

Cited by 14 | Viewed by 2806

Abstract

In this work we present the statistical and criticality analysis of the very low frequency (VLF) sub-ionospheric propagation data recorded by a VLF/LF radio receiver which has recently been established at the University of West Attica in Athens (Greece). We investigate a very recent, strong (M6.9), and shallow earthquake (EQ) that occurred on 30 October 2020, very close to the northern coast of the island of Samos (Greece). We focus on the reception data from two VLF transmitters, located in Turkey and Israel, on the basis that the EQ’s epicenter was located within or very close to the 5th Fresnel zone, respectively, of the corresponding sub-ionospheric propagation path. Firstly, we employed in our study the conventional analyses known as the nighttime fluctuation method (NFM) and the terminator time method (TTM), aiming to reveal any statistical anomalies prior to the EQ’s occurrence. These analyses revealed statistical anomalies in the studied sub-ionospheric propagation paths within ~2 weeks and a few days before the EQ’s occurrence. Secondly, we performed criticality analysis using two well-established complex systems’ time series analysis methods—the natural time (NT) analysis method, and the method of critical fluctuations (MCF). The NT analysis method was applied to the VLF propagation quantities of the NFM, revealing criticality indications over a period of ~2 weeks prior to the Samos EQ, whereas MCF was applied to the raw receiver amplitude data, uncovering the time excerpts of the analyzed time series that present criticality which were closest before the Samos EQ. Interestingly, power-law indications were also found shortly after the EQ’s occurrence. However, it is shown that these do not correspond to criticality related to EQ preparation processes. Finally, it is noted that no other complex space-sourced or geophysical phenomenon that could disturb the lower ionosphere did occur during the studied time period or close after, corroborating the view that our results prior to the Samos EQ are likely related to this mainshock. Full article

(This article belongs to the Special Issue Complex Systems Time Series Analysis and Modeling for Geoscience)

► Show Figures

Figure 1

17 pages, 3153 KiB

Open AccessEditor’s ChoiceArticle

Low-Frequency Seismic Noise Properties in the Japanese Islands

by Alexey Lyubushin

Entropy 2021, 23(4), 474; https://doi.org/10.3390/e23040474 - 16 Apr 2021

Cited by 9 | Viewed by 4348

Abstract

The records of seismic noise in Japan for the period of 1997–2020, which includes the Tohoku seismic catastrophe on 11 March 2011, are considered. The following properties of noise are analyzed: The wavelet-based Donoho–Johnston index, the singularity spectrum support width, and the entropy of the wavelet coefficients. The question of whether precursors of strong earthquakes can be formulated on their basis is investigated. Attention is paid to the time interval after the Tohoku mega-earthquake to the trends in the mean properties of low-frequency seismic noise, which reflect the constant simplification of the statistical structure of seismic vibrations. Estimates of two-dimensional probability densities of extreme values are presented, which highlight the places in which extreme values of seismic noise properties are most often realized. The estimates of the probability densities of extreme values coincide with each other and have a maximum in the region:

30 ° N \leq Lat \leq 34 ° N

136 ° E \leq Lon \leq 140 ° E

. The main conclusions of the conducted studies are that the preparation of a strong earthquake is accompanied by a simplification of the structure of seismic noise. It is shown that bursts of coherence between the time series of the day length and the noise properties within annual time window precede bursts of released seismic energy. The value of the lag in the release of seismic energy relative to bursts of coherence is about 1.5 years, which can be used to declare a time interval of high seismic hazard after reaching the peak of coherence. Full article

(This article belongs to the Special Issue Complex Systems Time Series Analysis and Modeling for Geoscience)

► Show Figures

Figure 1

11 pages, 1044 KiB

Open AccessArticle

On Time Scales of Intrinsic Oscillations in the Climate System

by Anastasios A. Tsonis, Geli Wang, Wenxu Lu, Sergey Kravtsov, Christopher Essex and Michael W. Asten

Entropy 2021, 23(4), 459; https://doi.org/10.3390/e23040459 - 13 Apr 2021

Cited by 1 | Viewed by 1880

Abstract

Proxy temperature data records featuring local time series, regional averages from areas all around the globe, as well as global averages, are analyzed using the Slow Feature Analysis (SFA) method. As explained in the paper, SFA is much more effective than the traditional Fourier analysis in identifying slow-varying (low-frequency) signals in data sets of a limited length. We find the existence of a striking gap from ~1000 to about ~20,000 years, which separates intrinsic climatic oscillations with periods ranging from ~60 years to ~1000 years, from the longer time-scale periodicities (20,000 year+) involving external forcing associated with Milankovitch cycles. The absence of natural oscillations with periods within the gap is consistent with cumulative evidence based on past data analyses, as well as with earlier theoretical and modeling studies. Full article

(This article belongs to the Special Issue Complex Systems Time Series Analysis and Modeling for Geoscience)

► Show Figures

Figure 1

13 pages, 3874 KiB

Open AccessArticle

Statistical Analysis of the Relationship between AETA Electromagnetic Anomalies and Local Earthquakes

by Qinmeng Guo, Shanshan Yong and Xin’an Wang

Entropy 2021, 23(4), 411; https://doi.org/10.3390/e23040411 - 30 Mar 2021

Cited by 7 | Viewed by 1748

Abstract

To verify the relationship between AETA (Acoustic and Electromagnetics to Artificial Intelligence (AI)) electromagnetic anomalies and local earthquakes, we have performed statistical studies on the electromagnetic data observed at AETA station. To ensure the accuracy of statistical results, 20 AETA stations with few data missing and abundant local earthquake events were selected as research objects. A modified PCA method was used to obtain the sequence representing the signal anomaly. Statistical results of superposed epoch analysis have indicated that 80% of AETA stations have significant relationship between electromagnetic anomalies and local earthquakes. These anomalies are more likely to appear before the earthquakes rather than after them. Further, we used Molchan’s error diagram to evaluate the electromagnetic signal anomalies at stations with significant relationships. All area skill scores are greater than 0. The above results have indicated that AETA electromagnetic anomalies contain precursory information and have the potential to improve local earthquake forecasting. Full article

(This article belongs to the Special Issue Complex Systems Time Series Analysis and Modeling for Geoscience)

► Show Figures

Figure 1

19 pages, 5707 KiB

Open AccessEditor’s ChoiceArticle

Non-Extensive Statistical Analysis of Acoustic Emissions: The Variability of Entropic Index q during Loading of Brittle Materials Until Fracture

by Andronikos Loukidis, Dimos Triantis and Ilias Stavrakas

Entropy 2021, 23(3), 276; https://doi.org/10.3390/e23030276 - 25 Feb 2021

Cited by 4 | Viewed by 1690

Abstract

Non-extensive statistical mechanics (NESM), introduced by Tsallis based on the principle of non-additive entropy, is a generalisation of the Boltzmann–Gibbs statistics. NESM has been shown to provide the necessary theoretical and analytical implementation for studying complex systems such as the fracture mechanisms and crack evolution processes that occur in mechanically loaded specimens of brittle materials. In the current work, acoustic emission (AE) data recorded when marble and cement mortar specimens were subjected to three distinct loading protocols until fracture, are discussed in the context of NESM. The NESM analysis showed that the cumulative distribution functions of the AE interevent times (i.e., the time interval between successive AE hits) follow a q-exponential function. For each examined specimen, the corresponding Tsallis entropic q-indices and the parameters β_q and

τ_{q}

were calculated. The entropic index

q

shows a systematic behaviour strongly related to the various stages of the implemented loading protocols for all the examined specimens. Results seem to support the idea of using the entropic index

q

as a potential pre-failure indicator for the impending catastrophic fracture of the mechanically loaded specimens. Full article

(This article belongs to the Special Issue Complex Systems Time Series Analysis and Modeling for Geoscience)

► Show Figures

Figure 1

9 pages, 2885 KiB

Open AccessArticle

Possible Correlations between the ULF Geomagnetic Signature and Mw6.4 Coastal Earthquake, Albania, on 26 November 2019

by Dragoș Armand Stănică and Dumitru Stănică

Entropy 2021, 23(2), 233; https://doi.org/10.3390/e23020233 - 17 Feb 2021

Cited by 4 | Viewed by 1757

Abstract

An earthquake of Mw6.4 hit the coastal zone of Albania on 26 November 2019, at 02:54:11 UTC. It was intensively felt at about 34 km away, in Tirana City, where damages and lives lost occurred. To emphasize a pre-seismic geomagnetic signature before the onset of this earthquake, the data collected on the interval 15 October–30 November 2019, at the Panagjurishte (PAG)-Bulgaria and Surlari (SUA)-Romania observatories were analyzed. Further on, for geomagnetic signal identification we used the polarization parameter (BPOL) which is time invariant in non-seismic conditions and it becomes unstable due to the strain effect related to the Mw6.4earthquake. Consequently, BPOL time series and its standard deviations are performed for the both sites using ultra low frequency (ULF)-fast Fourier transform (FFT) band-pass filtering. A statistical analysis, based on a standardized random variable equation, was applied to emphasize on the BPOL* (PAG) and ABS BPOL* (PAG) time series the anomalous signal’s singularity and, to differentiate the transient local anomalies due to the Mw6.4 earthquake, from the internal and external parts of the geomagnetic field, taken PAG observatory as reference. Finally, the ABS BPOL* (PAG-SUA) time series were obtained on the interval 1–30 November 2019, where a geomagnetic signature greater than 2.0, was detected on 23 November and the lead time was 3 days before the onset of the Mw6.4earthquake. Full article

(This article belongs to the Special Issue Complex Systems Time Series Analysis and Modeling for Geoscience)

► Show Figures